毫米波大规模MIMO系统中基于智能搜索的混合预编码算法

A Hybrid Precoding Algorithm Based on Intelligent Search in Millimeter Wave Massive MIMO Systems

为解决传统全连接结构毫米波大规模MIMO系统高硬件成本和实现难度大的问题,本文提出了一种基于智能搜索的部分连接结构混合预编码算法。该算法在基站端采用经典的迫零数字预编码,在模拟预编码部分单独设计模拟预编码矩阵,避免了数字、模拟预编码矩阵联合设计的高复杂度,并利用模拟预编码矩阵的块对角化特性,将其设计问题转化为最优化问题,采用SBO(satin bowerbird optimization)优化算法解决此问题。针对原始SBO算法易陷入局部最优的缺点,提出了一种基于动态突变概率的DSBO(satin bowerbird optimization based on dynamic mutation probability)算法。针对移相器分辨率有限的情况,改进了DSBO算法,使之能解决此离散优化问题。仿真结果表明,与其他现有算法相比,提出的算法具有更高的系统容量和更低的误码率,且能处理移相器分辨率有限的情况。

In order to solve the problem of high hardware cost and difficult implementation in traditional fully connected millimeter wave massive MIMO systems, a partially connected hybrid precoding scheme based on intelligent search algorithm is proposed. In this algorithm, the classical zero-forcing digital precoding scheme is used at the base station, and the analog precoding matrix is designed separately in the part of analog precoding, which avoids the high complexity of the joint design of the digital and analog precoding matrix. After that, the block diagonalization property of analog precoding matrix is made use of to transfer the problem of designing analog precoding matrix to the problem of optimization, which is to be solved by Satin Bowerbird Optimization. Aiming at making up the shortcoming of original SBO in searching global optimum, an algorithm called DSBO is proposed. In the case that phase shifters’ resolution is limited, DSBO is improved to solve this discrete optimization problem. The simulation results show that the scheme proposed presents competitive system capacity as well as a relatively low bit error rate, and is able to handle the case that phase shifters’ resolution is limited.